{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Uploading data (.dta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "use \"https://github.com/SaoriIwa/Stata-IE-Visual-Library/raw/master/Library/RD%20plots/Regression%20discontinuity%20plots%20with%20confidence%20intervals/data.dta\", clear"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Calculating cutoff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "qui sum \tcutoff\n",
    "local \tcutoff = r(mean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Creating the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "This front-end cannot display the desired image type."
      ]
     },
     "metadata": {
      "image/png": {
       "height": 436,
       "width": 600
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "twoway  (lpolyci tmt_status pmt_score if pmt_score < `cutoff', clcolor(navy) acolor(gs14)) || ///\n",
    "\t\t\t(lpolyci tmt_status pmt_score if pmt_score > `cutoff', clcolor(navy) acolor(gs14)), ///\n",
    "\t\t\txline(`cutoff', lcolor(red) lwidth(vthin) lpattern(dash)) ///\n",
    "\t\t\tytitle(Probability of receiving treatment) ///\n",
    "\t\t\txtitle(Proxy means test score) ///\n",
    "\t\t\tlegend(off) ///\n",
    "\t\t\tbgcolor (white) graphregion(color(white))  ///\n",
    "\t\t\tnote(\"Note: gray area is 95% confidence interval.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Exporting the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "qui gr export \"figure.png\", width(5000) replace"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Stata",
   "language": "stata",
   "name": "stata"
  },
  "language_info": {
   "file_extension": ".do",
   "mimetype": "text/x-stata",
   "name": "stata"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
